Technovation With Peter High

1048: What if the hiring process wasn’t broken—but reimagined? Anthony Moisant, Chief Information Officer and Chief Security Officer at Indeed, details how his teams are building trusted systems, tackling AI bias, and leveraging background agents and AI sourcing to solve the “black hole” of hiring. He also reflects on the importance of early-career talent, skill-based hiring, and the balance of self-learning and leadership-led growth. The conversation covers: Why trust is foundational to AI innovation at Indeed How “invite to apply” transforms the candidate experience The future of work through agentic systems and AI sourcing Balancing self-driven learning with leadership-created space

1047: What does it take to lead tech—and the enterprise—in 2026? In this episode of Technovation, we feature a panel from our October 2025 Metis Strategy Summit where Steven Norton speaks with three top executive recruiters: Craig Stephenson (Korn Ferry), Jamey Cummings (JM Search), and Scott Robbin (Heidrick & Struggles). Throughout the conversation, each recruiter gives their perspective on the evolving mandate of the CIO. The conversation covers: The convergence of data, security, digital, and operations under the CIO How talent strategy and succession planning are changing What makes a technology leader board-ready The rise (and ambiguity) of the Chief AI Officer Offshore workforce trends and leadership development

Enterprises aren’t failing at AI. They’re failing at data. Daniel Docter, Managing Director at Dell Technologies Capital, shares why the biggest barrier to enterprise AI isn’t models or talent—it’s the fractured, unstructured, and context-free data that most companies still struggle to harness. In this episode of Technovation, Daniel and Peter High explore: Why data context is critical to enabling enterprise reasoning How Redis and other startups are fixing the AI performance gap What Dell Technologies Capital looks for in early-stage enterprise AI How corporate VC has evolved into a founder-enabling force Why the next five years will reward enterprises that fix their data layer

Digitization was just the first step. True digital transformation in healthcare is only beginning. Dr. Michael Pfeffer, Chief Information and Digital Officer at Stanford Health Care, shares how he and his team are moving beyond electronic health records to deliver real-time, AI-powered care. From building ChatEHR, a secure, embedded LLM interface, to developing Stanford’s FIRM framework for responsible AI, Pfeffer provides a behind-the-scenes look at one of the nation’s most advanced digital health systems. In this episode, you’ll learn: Why “digitized” isn’t the same as “digital” How Stanford built the first integrated LLM in clinical workflows What makes healthcare AI safe, useful, and equitable Where AI adds real clinical value and where it doesn’t The vision behind precision health at scale

1045: AI is no longer a side experiment—it’s a core capability. But are your people, partnerships, and governance models ready for it? In this special Metis Strategy Summit panel episode, three seasoned technology leaders explore what it really takes to build trust, scale talent, and lead responsibly in the age of AI: Paul Ballew, Chief Data & Analytics Officer, National Football League Lakshman Nathan, EVP & CIO, Paramount Mark Sherwood, EVP & CIO, Wolters Kluwer Moderated by Peter High, the conversation dives into transformation through the lens of distributed governance, workforce readiness, and the human element behind every AI ambition. Key themes from the panel include: How the NFL’s “One-to-One” fan engagement model blends personalization and privacy What happens when $2B in savings depends on department-level AI strategy (Paramount) Why “value realization” starts with your CFO and ends with trust (Wolters Kluwer) The limits of centralization—and why distributed innovation m

What happens when a former startup CEO brings performance management discipline into city government? In this episode of Technovation, Peter High speaks with San José Mayor Matt Mahan about applying data-driven decision-making, KPIs, and accountability—practices familiar to tech leaders—to the public sector. Drawing from his experience running venture-backed startups, Mahan explains how focus, measurement, and feedback loops are reshaping how City Hall operates. Key topics include: Applying startup-style performance management to government Using dashboards and metrics to improve accountability Prioritizing outcomes over activity Leveraging AI to improve city services at scale Building a workforce ready to use new technology responsibly

How do you build and scale digital innovation inside a 170-year-old company? Luke Gebb, EVP of Global Innovation at American Express, joins Peter High to share how Amex Digital Labs brings emerging technologies to market through a disciplined stage-gate process. Gebb outlines how his team incubates and graduates products that become core to Amex’s customer experience—from peer-to-peer payments to blockchain-based travel rewards. He also shares lessons in navigating cross-functional execution, partnering with big tech, and launching products customers actually use. Key topics include: Amex’s stage-gate innovation model Scaling peer-to-peer payments via PayPal/Venmo Building customer-centric discovery tools with GenAI Passport: Using NFTs to enhance travel experience Collaborating across engineering, legal, and compliance ” Discount your AI ROI because mileage always varies Learn more

AI can’t fix what the healthcare system fundamentally gets wrong. In this episode, Liam Donohue, Co-Founder and Managing Partner at 406 Ventures, shares why his firm is betting on value-based care—and why AI risks breaking the system if applied to the wrong incentives. From launching EdTech’s earliest funds to shaping 406 Ventures’ sector focus in healthcare, cybersecurity, and infrastructure, Liam offers hard-won lessons in disciplined investing, operator-first teams, and systemic transformation. Key highlights: Why fee-for-service economics undermine care innovation How value-based care reshapes both incentives and outcomes The real reason AI is booming in revenue cycle management Lessons from WelbeHealth: rethinking elder care and payments Liam’s take on what makes a founder truly backable

What if AI is repeating the same mistakes society made during the Industrial Revolution? In this episode of Technovation, Peter is joined by Nobel Prize Laureate in Economics and Ronald A. Kurtz Professor of Entrepreneurship at the MIT Sloan School of Management Simon Johnson. Throughout their conversation, they explore why automation has historically failed to deliver shared prosperity and why artificial intelligence may be following the same path. Drawing on centuries of economic history, Johnson explains how mechanization once displaced workers faster than new jobs were created, fueling inequality and social unrest. Together, they discuss what today’s AI leaders must learn from history, why institutions matter more than technology alone, and how workforce anxiety is an early warning sign of deeper structural problems. Key topics include: Automation vs. job creation AI’s impact on entry-level and knowledge work Workforce polarization and regional inequality Lessons from the Industrial Revolution for today’

Most enterprises aren’t struggling with AI because of technology. They’re struggling because they’re trying to scale pilots instead of platforms. In this episode of Technovation, Peter High speaks with Atilla Tinic, CIO of Qualcomm, about how the company is moving beyond one-off AI use cases to build an enterprise AI platform designed for scale. Tinic explains why unified and validated data is essential for AI accuracy, how Qualcomm enables developers and business teams through a centralized AI marketplace, and why security must be embedded into AI architecture from day one. Key topics include: Why data governance is foundational to AI success How Qualcomm structures AI as a reusable enterprise platform The rise of AI agents and autonomous systems Cybersecurity challenges introduced by AI and how AI helps defend against them

What does it actually take to move AI from experimentation to enterprise-wide impact? In this episode of Technovation, Peter High speaks with Leigh-Ann Russell, Chief Information Officer and Global Head of Engineering at Bank of New York (BNY), about how one of the world’s most systemically important financial institutions is operationalizing AI at scale. Leigh-Ann shares how BNY trained 99% of its 50,000-person workforce on AI, moved beyond pilots into deep enablement, and empowered employees across technical and non-technical roles to build AI agents that drive real productivity gains. Key topics discussed include: Training nearly the entire workforce to become AI-literate Moving from AI pilots to enterprise-wide enablement Empowering employees to build and deploy AI agents Reducing cognitive load while improving speed and resilience Leading AI adoption through hands-on executive behavior

What if the key to enterprise AI wasn’t a tool, but a mindset? Mark Bloom, Global CIO at AJ Gallagher, joins Technovation to share how the 70,000-person insurance giant is scaling AI by leading with data quality and cultural alignment—not flashy tools. In this episode, Bloom details: How Gallagher eliminated 800+ data silos to centralize insight and enable AI Why crowdsourcing use cases from employees unlocked adoption at scale The shift from efficiency gains to revenue-focused AI How culture helped overcome resistance to data consolidation His dual perspective as both CIO and board member

What really drives cybersecurity investment and why is “threat” often the last reason? In this episode, Rakesh Loonkar, co-founder of Transmit Security and general partner at Picture Capital, shares a contrarian take on how cybersecurity product categories emerge and why compliance and platform shifts often matter more than actual threats. Drawing on decades of experience as both operator and investor, Rakesh explains how he evaluates risk timing, founder mindset, and market inflection points. Key highlights from the episode: Why most cyber spend starts with compliance, not attacks How to invest ahead of platform shifts like AI and cloud A three-part model for understanding cyber spending behavior The risks of financial-only boards in technical startups Lessons from building Trusteer, Transmit, and Picture Capital

What if your AI strategy is your business strategy? In this episode, three top tech leaders share how they’re embedding AI not as a standalone initiative, but as a lever for enterprise transformation. Mojgan Lefebvre (Travelers), Pawan Verma (Cencora), and Glenn Remoreras (Breakthru Beverage) reveal how they’ve partnered with boards, business units, and frontline teams to scale AI from proof of concept to performance. Highlights include: How Travelers reduced onboarding from 2 hours to 2 minutes Cencora’s framework for board-level AI education Breakthru’s use of summits to build AI literacy across leadership The role of generative AI in operational redesign Balancing experimentation with responsible governance

What does it really take to design for resilience in an AI-first world? In this panel from the Metis Strategy Summit, Amtrak CDO Judith Apshago, GE Aerospace CIO David Burns, and Zoetis CDTO Keith Sarbaugh explore how resilient infrastructure is becoming the backbone of enterprise trust, uptime, and AI scalability. Tune in to learn how these leaders are: Responding to cloud outages and software disruption in real time Building AI literacy, governance, and use-case portfolios at scale Extending cyber defense and IT support to vulnerable supply chain partners Using edge computing and sensors to enable predictive diagnostics Converging IT and OT teams to enhance infrastructure intelligence

1036: What does it mean to manage a digital workforce? In this episode of Technovation, we feature a panel from our most recent Metis Strategy Summit where three top executives explore how AI is reshaping work, both automating tasks, and changing the nature of management itself. Peter High speaks with: Jennifer Charters, Chief Information Officer at Lincoln Financial Prasanna Gopalakrishnan, Chief Product & AI Officer at ADP Daniel Marcu, Global Head of AI Engineering at Goldman Sachs Together, they discuss: Why AI agents require new thinking about team structure and oversight How CIOs and CHROs must partner to build enterprise AI fluency The risks of shadow AI and the need for secure platforms How habit loops and performance incentives impact AI adoption What it takes to balance innovation speed with organizational readiness

Our broadcast today features a panel from our most recent Metis Strategy Summit on the topic of Delivering the Product Operating Model (and Mindset) at Scale. In this panel episode, we explore the limits and lessons of scaling the product operating model. Sal Companieh (Cushman & Wakefield), Jim Fowler (Nationwide), and Diane Schwarz (Smurfit WestRock) reflect on where product thinking thrives and where it breaks down. Here are 5 takeaways from their candid discussion: Why “readiness” must come before model The risks of forcing product teams into fragmented structures When to co-create with business leaders—and when to slow down How agile funding models can clash with CapEx culture What to do when the organization “doesn’t want the service”

What if the most defensible companies of the AI era aren’t the ones building the infrastructure—but the ones using it to rethink workflows? In this Technoventure episode, Peter High speaks with Jaime Montgomery, Founder and Managing Partner of March Capital, about why the firm is investing heavily in the AI application layer—not chips, not clouds, but the companies delivering real task-based outcomes. Key topics explored: Why workflow-based moats beat data moats in the new venture cycle How application-layer companies are scaling faster with leaner GTM The ripple effects of AI CapEx on the U.S. economy and tax base March Capital’s bets on open-source LLMs and scientific discovery Why Montgomery believes AI “bailed out” the U.S. and VC industry alike

What’s stopping AI from scaling across the enterprise? For Madhu Ramamurthy, CIO of Zurich North America, it’s not the technology. It’s the culture. In this episode, Madhu shares how he’s navigating the paradox of AI: a tool with unprecedented potential, surrounded by institutional resistance, unclear regulations, and cultural misalignment. He outlines Zurich’s approach to responsible AI deployment, organizational change, and ethical tech use. Key highlights include: How “organizational antibodies” can kill innovation before it scales The case for explainability and governance in AI development Why domain expertise is more valuable than tech fluency Building AI-native teams outside of legacy systems Madhu’s warning on digital flattery and sycophantic AI

What does it really take to scale AI across a global enterprise? In this episode, Jaime Montemayor, Chief Digital and Technology Officer at General Mills, shares the AI playbook behind the company’s digital transformation from foundational investments in cloud and data governance to business-led innovation across supply chain, e-commerce, and marketing. With 96% of General Mills’ supply chain data now clean and governed, Jaime’s team is shifting from predictive analytics to agentic architectures that enable scalable, AI-powered automation. Key insights include: Why cloud migration came before ERP modernization How trust and business integration drive AI adoption Building a connected data foundation to serve every segment Agentic AI use cases in supply chain and marketing Org design strategies to “lift and shift” innovation at scale